Hi Mike,

Thank you for your question! We're targeting M103 to start the experiment.
So, IIUC, it would not interact with the double-key experiment running
through M102 unless it's extended.


On Wed, Apr 27, 2022 at 5:55 AM Mike Taylor <miketa...@chromium.org> wrote:

> Hi Daisuke,
>
> Can you clarify the timeline of the experiment? Would it begin in M103? I
> have concerns about interactions with the current double-key experiment
> <https://groups.google.com/a/chromium.org/g/blink-dev/c/WQtp7Ixd1RU>
> we're running for Network State Partitioning in M101 and M102.
>
> On 4/26/22 7:59 AM, Daisuke Enomoto wrote:
>
> Contact emails
>
> ri...@chromium.org, nidhij...@chromium.org, denom...@chromium.org
>
> Explainer
>
>
> https://docs.google.com/document/d/1pvaMg7J5beBXD7trzHJH_MDULc_wRHLx40MFYAmjknE/edit
>
> Specification
>
> N/A (because there are no web-exposed changes)
>
> Summary
>
> This limited experiment measures how much "pervasive payloads" contribute
> to the performance impact of the split HTTP cache in each Chrome channel
> over a three-week period. Pervasive payloads are those third-party payloads
> included on at least 500 sites and fetched at least 10M times in a month,
> based on Chrome's analysis (payload list included below). This experiment
> further measures the impact on Core Web Vitals metrics of restoring
> pervasive payloads (and only pervasive payloads) to a single-keyed cache
> regime. The privacy benefits of the split HTTP cache are preserved.
>
> Blink component
>
> Blink>Network
> <https://bugs.chromium.org/p/chromium/issues/list?q=component:Blink%3ENetwork>
>
> Motivation
>
> Browsers split HTTP caches based on the top-frame visited origin
> (“double-keyed” or "triple-keyed" caching) to prevent sites from tracking
> users via a timing attack on a cross-site client cache.
>
> Chrome’s analysis estimates that split caching results in a 3% increase in
> cache misses, i.e. fetches for which a payload exists in the cache of the
> user's device, but is unavailable to the page because it was fetched by the
> user while loading a page from a different origin. This results in
> approximately 4% more total bytes being fetched over the network.
>
> Our analysis further revealed that many of the redundant fetches caused by
> split caching were for common payloads associated with displaying user
> content (libraries, fonts, widgets, ads) or common payloads that assist in
> operating online businesses (analytics). The delayed arrival of these
> common payloads resulted in visible "jank" for users, impacting performance
> metrics like LCP <https://web.dev/lcp>, FCP <https://web.dev/fcp> and CLS
> <https://web.dev/cls/>. This jank has been associated with negative
> effects to online business' engagement and conversion rates. Furthermore,
> delayed loads of analytics and ads payloads can result in missed ads
> impressions and dropped analytics hits.
>
> Initial public proposal
>
> This experiment sends a list to Chrome of 100 <URL, hash> pairs whose
> payloads are considered pervasive (the "pervasive payloads list"). During
> the three-week experiment period, if Chrome fetches a payload that matches
> both the URL and its hash on the pervasive payloads list, it is inserted
> into a local single-keyed cache. This payload is then available for use by
> Chrome when loading pages on other sites that include the matching URL. All
> other fetches for URLs not on the pervasive payloads list are cached
> according to the existing split HTTP cache.
>
> The hash covers the payload body and most response headers, except for
> those which change on every response.
>
> To ensure we do not degrade the privacy profile of any users during this
> experiment, only users with third-party cookies currently enabled will be
> eligible for the experiment. We will compare the experience of users in
> experiment and control arms according to total bytes loaded and page
> performance metrics like the Core Web Vitals <https://web.dev/vitals>.
>
> The pervasive payloads list was produced by crawling the web and
> aggregating the most commonly referenced third-party resource URLs included
> in HTML content. We then used pseudonymous URL-keyed metrics from Chrome to
> estimate the traffic to sites and the number of impressions of third-party
> resources. Individually identifiable browsing or search histories were not
> used in the creation of the pervasive payload list (for more information
> about Chrome's data collection policies and privacy policies, see
> google.com/chrome/privacy). The resulting list was further filtered for
> any URLs that might contain PII (e.g. URLs with extensive or opaque query
> parameters). The list was also manually reviewed to ensure it included only
> payloads reasonably expected to be pervasive; the manual review did not
> result in any payloads being removed.
>
> The privacy properties of the split HTTP cache are considered essential to
> users and this proposal intends to maintain those properties, specifically
> by maintaining split HTTP caching for all payloads not on the pervasive
> payloads list.
>
> API semantics are unchanged. User-facing functionality is unchanged
> (though we expect performance to be slightly improved).
>
> The list of the top 100 Pervasive URLs for use in this experiment is
> pending internal reviews and will be shared on this thread upon approval.
> Future directions
>
> This experiment is the first step in a path exploring improved handling of
> pervasive payloads in the browser cache. We outline the intended future
> functionality here to clarify the intentions behind the current experiment.
> The overview below is not complete or final and subsequent parts of the
> design and implementation will be presented and discussed in further
> Intents to Experiment and Prototype.
>
> At a high level, a future improvement to the handling of pervasive
> payloads may involve:
>
>
>    -
>
>    Assembling a list of pervasive payloads that meets the following
>    criteria:
>    -
>
>       Maintains the privacy of user browsing histories in its creation
>       -
>
>       Fairly represents pervasive payloads as they have been chosen by
>       developers on the web, not payloads selected or favored by any 
> particular
>       library or browser vendor.
>       -
>
>          This experiment will initially use a static list of predefined
>          URLs assembled as described in the 'Initial public proposal' section 
> above
>          -
>
>          A future implementation will likely dynamically update the
>          payloads list on, for example, a weekly cadence.
>          -
>
>    Implementing shared caching for pervasive payloads that meets the
>    following criteria:
>    -
>
>       Materially improves load times and responsiveness for web users
>       (under study in this experiment)
>       -
>
>       Does not create a new tracking vector based on cache timing attacks
>       -
>
>       Does not require users to fetch payloads before the browser knows
>       they will need it (i.e. we don't plan to bundle payloads with browser
>       installs or updates)
>       -
>
>       Does not increase local storage required by browser installs or
>       caches
>
>
> To privately and fairly assemble the list of pervasive payloads, we are
> exploring the use of Private Heavy Hitters
> <https://www.tensorflow.org/federated/tutorials/private_heavy_hitters>.
> To implement a privacy-preserving shared cache after the deprecation of
> third-party cookies, we are exploring adding a measure of randomness to the
> observed presence or absence of a pervasive payload in the shared cache.
>
> However, this work is only worthwhile if it results in materially improved
> load times for real users. This Intent to Experiment covers only whether or
> not we should attempt to measure the performance gains that might be
> realized if pervasive payloads were placed in a shared cache, as one data
> point among others that will contribute to discussions about future steps
> for the proposal.
>
> TAG review
>
> None yet.
>
> TAG review status
>
> N/A
>
> Risks
> Interoperability and Compatibility
>
> Chrome's compliance with the relevant standards is unchanged. Caching
> behavior differs between browsers so interoperability will not be affected.
>
> The list of popular payloads is specifically chosen to minimize
> compatibility risks.
>
>
> Gecko: No signal
>
> WebKit: No signal
>
> Web developers: No signals
>
> Other signals:
>
> WebView application risks
>
> Does this intent deprecate or change behavior of existing APIs, such that
> it has potentially high risk for Android WebView-based applications? No
>
>
> Debuggability
>
> There is no developer-exposed API for this feature, so most DevTools
> support is not relevant. It would be useful to indicate whether a resource
> was served from the single-keyed cache in the network tab, however this
> will not be implemented in the initial experiment.
>
> Security and privacy
>
> Single-keyed caching introduces global state shared between different
> browsing contexts. A shared cache can introduce information leaks based on
> cache probing (https://xsleaks.dev/docs/attacks/cache-probing/),
> including XS-Search (https://xsleaks.dev/docs/attacks/xs-search/) in
> applications which conditionally load a single-keyed-cache eligible
> resource based on authenticated user state. The state of the cache, queried
> across different contexts, could also be used as a fingerprint, permitting
> user tracking; however, in this case, we believe this does not provide
> tracking capabilities beyond those of third-party cookies.
>
> To protect users during this experiment, we limit the experiment
> population to those users with third-party cookies enabled. Recognizing
> that third-party cookies will eventually be switched off for most users
> <https://privacysandbox.com/>, we are developing protections such as
> slightly randomizing cache hit/miss checks, disallowing eviction, or
> guaranteeing attempts to read from the cache reliably populate that cache
> entry. These protections will be proposed and incorporated before any
> future optimizations are launched.
>
> For the purposes of the current experiment, we will be using the same
> implementation of single-keyed caching that Chrome used before the HTTP
> cache was partitioned in M77 (
> https://chromestatus.com/feature/5730772021411840).
>
> To summarize, the security and privacy restrictions on this experiment are
> as follows:
>
>
>    1.
>
>    We will exclude users that have third-party cookies disabled.
>    2.
>
>    Only a small percentage of users will be included in the experiment,
>    reducing the likelihood and impact of any attacks abusing the single-keyed
>    cache.
>    3.
>
>    We will strictly limit the duration of the experiment on each channel
>    to 3 weeks.
>    4.
>
>    We will only serve pervasive resources from the single-keyed cache.
>    5.
>
>    We can turn off the experiment immediately (independent of browser
>    updates) if any other threats appear.
>
>
> Is this feature fully tested by web-platform-tests
> <https://chromium.googlesource.com/chromium/src/+/master/docs/testing/web_platform_tests.md>
> ?
>
> This behavior is specific to Chrome and not part of any standard, so it
> will not be tested in web platform tests.
>
> Flag name
>
> CacheTransparency
>
> Requires code in //chrome?
>
> No, but the list of popular payloads and the mechanism for distributing it
> to the browser will be Chrome-specific.
>
> Tracking bug
>
> https://bugs.chromium.org/p/chromium/issues/detail?id=1309002
>
> Launch bug
>
> https://bugs.chromium.org/p/chromium/issues/detail?id=1309353
>
> Estimated milestones
>
> M103 for off-by-default experiment
>
> Link to entry on the Chrome Platform Status
>
> https://chromestatus.com/feature/5768521127559168
>
>
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